Results 61 to 70 of about 95,703 (260)

Unsupervised Classification for Polarimetric Synthetic Aperture Radar Images Based on Wishart Mixture Models

Leida xuebao, 2017
Unsupervised classification is a significant step inthe automated interpretation of Polarimetric Synthetic Aperture Radar (PolSAR) images. However, determining the number of clusters in this process is still a challenging problem. To this end, we propose
Zhong Neng, Yang Wen, Yang Xiangli, Guo Wei   +3 more
doaj   +1 more source

Unsupervised Machine Learning Identifies Shared Biomechanical and Clinical Variation in Individuals with Knee Osteoarthritis and High BMI: A Secondary Analysis of the IDEA Trial

Arthritis Care &Research, Accepted Article.
Objective High body mass index (BMI≥27 kg/m2) and aberrant gait biomechanics are primary risk factors for knee osteoarthritis (KOA), yet the specific loading patterns linked to clinical disease features remain unclear. Unsupervised machine learning (ML) was used to identify vertical ground reaction force (vGRF) waveform modes of variation and ...
Ashley N. Buck, J. Elyse Borgert, Hyeon Lee, Liubov Arbeeva, Yvonne M. Golightly, Richard F. Loeser, Leigh F. Callahan, Stephen P. Messier, Brian Pietrosimone, Amanda E. Nelson, James S. Marron   +10 more
wiley   +1 more source

Classification Method for Surface Defects of Strip Steel Based on Dynamic Joint Weighting [PDF]

Jisuanji gongcheng
The surface quality of strip steel is an important indicator of the quality of steel products. Research on the classification of surface defects throughout the production process can reduce the occurrence of surface defects and improve the accuracy of ...
WANG Ya, GAN Qingsong, SHEN Qi, SONG Yuqing, LIU Yi, HAN Kai, LIU Zhe
doaj   +1 more source

An unsupervised method for social network spammer detection based on user information interests

Journal of Big Data, 2022
Online Social Networks (OSNs) are a popular platform for communication and collaboration. Spammers are highly active in OSNs. Uncovering spammers has become one of the most challenging problems in OSNs.
Darshika Koggalahewa, Yue Xu, Ernest Foo
doaj   +1 more source

Climate Classifications: the Value of Unsupervised Clustering

Procedia Computer Science, 2012
AbstractClassifying the land surface according to different climate zones is often a prerequisite for global diagnostic or predictive modelling studies. Classical classifications such as the prominent K̈oppen–Geiger (KG) approach rely on heuristic decision rules.
Jakob Zscheischler, Miguel D. Mahecha, Stefan Harmeling   +2 more
openaire   +4 more sources

Additively Manufactured Geometry‐Reconfigurable Soft Neural Probes With Monolithic Multifunctionality

Advanced Functional Materials, EarlyView.
A geometry‐reconfigured additive manufacturing strategy converts planar printed soft materials into soft compact neural probes with integrated hydrogel electrodes and microfluidic channels. The resulting NeuroMAP platform enables scalable multichannel recording, localized chemical delivery, stable in vivo electrophysiological recording, and reduced ...
Hyunjin Lee, Xinyi Wang, Sirui Li, Jihyang Park, Hyunseok Lee, Jianting Yao, Kedar Narayan, Yuqi Wang, Jiashu Ren, Yueqi Deng, Salahuddin Ahmed, Denver I. Greenawalt, Archana Pandiyan, Loganathan Veeramuthu, Chi‐Ching Kuo, Tao Zhou   +15 more
wiley   +1 more source

Improvements to the gastric cancer tumor-node-metastasis staging system based on computer-aided unsupervised clustering

BMC Cancer, 2018
Background The Union for International Cancer Control (UICC) tumor-node-metastasis (TNM) classification is a key gastric cancer prognosis system. This study aimed to create a new TNM system to provide a reference for the clinical diagnosis and treatment ...
Zhiqiong Wang, Mo Li, Zhen Xu, Yanlin Jiang, Huizi Gu, Ying Yu, Haitao Zhu, Hao Zhang, Ping Lu, Junchang Xin, Hong Xu, Caigang Liu   +11 more
doaj   +1 more source

LEAD: Literature Enhanced Ab Initio Discovery of Nitride Dusting Layers for Enhanced Tunnel Magnetoresistance and Lower Resistance Magnetic Tunnel Junctions

Advanced Materials, EarlyView.
Magnetic tunnel junctions (MTJs) using MgO tunnel barriers face challenges of high resistance‐area product and low tunnel magnetoresistance (TMR). To discover alternative materials, Literature Enhanced Ab initio Discovery (LEAD) is developed. The LEAD‐predicted materials are theoretically evaluated, showing that MTJs with dusting of ScN or TiN on ...
Sabiq Islam, William S. Rogers, Chen‐Yu Hu, Ming‐Yuan Song, Xinyu Bao, Shehrin Sayed, Jean Anne C. Incorvia   +6 more
wiley   +1 more source

Neuromorphic Electronics for Intelligence Everywhere: Emerging Devices, Flexible Platforms, and Scalable System Architectures

Advanced Materials, EarlyView.
The perspective presents an integrated view of neuromorphic technologies, from device physics to real‐time applicability, while highlighting the necessity of full‐stack co‐optimization. By outlining practical hardware‐level strategies to exploit device behavior and mitigate non‐idealities, it shows pathways for building efficient, scalable, and ...
Kapil Bhardwaj, Roshni Satheesh Babu, Yuxin Xia, Eva Bestelink, Radu Sporea, Nikos Hastas, Ioannis Zeimpekis, Dimitra G. Georgiadou, Sayani Majumdar   +8 more
wiley   +1 more source

Organic Materials of Tomorrow: Horizons of Artificial Intelligence

Advanced Materials, EarlyView.
This review examines machine learning techniques accelerating the discovery of organic semiconductors by linking molecular structure to properties. Key methods include graph neural networks, generative models, and active learning. Applications to organic photovoltaics demonstrate practical impact.
Harold Mena, J. Terence Blaskovits, Kun‐Han Lin, Denis Andrienko   +3 more
wiley   +1 more source